Comprehensive probability method of buffer insertion based on Gaussian fitting under process variation condition. (April 2023) - Wang, Xinsheng; Song, Yanhong; Yu, Mingyan
Abstract: A fast buffer insertion methodology based on comprehensive probability is proposed to solve the buffer insertion problem under the process variation condition. In the condition of considering the correlation between the required arrival time and downstream loading capacitance, the computation is large and complexity. We develop a fast and efficient Gauss-Hermite Quadrature and Gaussian fitting algorithm to solve it. Specially, we can use the mean of metric (required arrival time or performance cost ratio) based Gaussian fitting to get the optimal buffer insertion solution based on comprehensive probability. We verify our buffer insertion algorithm using timing analysis with both device and interconnect variations based on different circuits and metrics, and show that compared to reference's buffer insertion algorithm, our new buffer insertion methodology can obtain concordant results, but can greatly reduce the computation complexity.